As today’s big data world keeps growing, reference data keeps increasing in adoption. In financial trading, about 70 percent of all data used for business transactions are reference data sets. Some more examples of reference data include postal codes, country codes, and more. The use cases of reference data now apply to industries like education, corporate governance, and engineering. This article delves into reference data management (RDM), its processes, and the benefits for data consumers and other related stakeholders.
Table of Contents
Reference Data Defined
There are numerous definitions for reference data. The most common is the relation to a business’ metadata. Generally, any data used to categorize other data in a company’s database can be classified as reference data. It covers a wide range of data values and has many characteristics. One of the main features of reference data is its static nature. This is why it typically applies to static identifiers like code lists and currencies.
Today, many companies use reference data in their daily business operations to optimize data use and access for data users.
Given all this about reference data, what is reference data management? Reference data management uses reference data to create and manage data classifications.
Modern businesses collect vast amounts of data from disparate sources, making reference data management a go-to when it comes to leveraging big data for enhanced efficiency. It takes reference data management to make meaning out of a company’s unstructured and structured data. Reference data is also used in master data management (MDM) solutions to fuel manual and automated resources.
Two main types of reference data include internal and external reference data. Internal data exists inside a company’s enterprise and may require no external authority in its use. All other reference data outside of a company’s data enterprise is external reference data. These two have distinct characteristics, but efficient RDM solutions map both to ensure data reporting and governance accuracy.
How it Works
The reference data management process comprises three steps. The first step in reference data management involves data consolidation. This stage necessitates businesses to integrate all their reference data into a central repository. Here, data managers use standardization methods to categorize a company’s reference data into a comprehensive list. The comprehensive list can then be analyzed conveniently by data stewards in the next stage.
The second stage ensures quality checks in the reference data before it becomes access-worthy for data consumers. In ensuring data quality, data professionals use codes to identify and reconcile duplicates in the reference data. Distribution of the reference data is the final stage of the RDM process. Data users typically want hassle-free access to datasets, and this is often the priority of data managers in distributing reference data across a data enterprise.
Main Benefits
Business entities have a lot to gain from RDM solutions. Some specific RDM benefits include the following:
Ensures Data Quality
RDM can help drive efficiency across a data enterprise ensuring high levels of data quality. The data standardization and governance efforts involved in the RDM process help create consistency across an RDM system, making it easy to use. Without data quality, businesses can be at risk of invalid business choices and decisions. Timely and accurate information is a must-have for data users at all times.
Empowers Data Users
The world is constantly evolving, and data users increasingly want to do more with less. A company’s data set is only as beneficial as the ease with which users can access it. With RDM’s central repository, it becomes easier for managers of data to build a user-friendly infrastructure applicable to all data sets irrespective of source, format, etc. This can ramp up the value data users derive from a company’s data warehouse. Eliminating the barriers to data access means pushing the limits to which data can be used in real time.
Creates Resilience
Business resilience requires business leaders to be highly responsive to challenges and opportunities as they arise. With the convenience and data quality attributes associated with reference data, businesses can use RDM solutions to ensure the resilience of their processes and operations.